zoektocht naar erfelijke metabole aandoening (dutch)/ solve the unsolved (english)

Conditions: Inherited Metabolic Disorders

Summary: the goal of this clinical trial is to integrate genomic (wes/wgs) and other -omics technologies in order to find the genetic causes, in 500 patients (children and adults) with an unexplained metabolic phenotype in whom standard care (genetic and metabolic evaluation) did not provide a diagnosis. the overall aim of this study is to diagnose patients with an unknown metabolic phenotype. in addition, we want to provide evidence that the combination of approaches and techniques used in this study will increase diagnostic yield compared to current separated approaches. all participants will undergo a multi-omics(wes, wgs and metabolomics) approach to solve the unsolved genetic basis of their metabolic phenotype.

rationale: inborn errors of metabolism (iem) are monogenic conditions in which the impairment of a biochemical pathway is intrinsic to the pathophysiology of the disease. organ dysfunction results from intoxication and/or storage of metabolites, as well as a shortage of energy and building blocks. rapid diagnosis of iem enables initiation of targeted treatment (e.g. diet) slowing down or stopping the degenerative nature of the disease, resulting in significantly reduction of morbidity and mortality. a diagnosis also enables prognostication, access to community services and accurate genetic counselling for the patient and his/her family. diagnosing iem can be a major challenge, because of phenotypic heterogeneity and complex, expensive, diagnostic tests. whole exome/ genome sequencing (wes/wgs) has revolutionized diagnostics of rare diseases and iem, but still gives a negative or inconclusive result in \>50% of cases. addition of other omics technologies (metabolomics, glycomics, lipidomics, epigenomics, transcriptomics, proteomics) with integrated bioinformatics increases diagnostic yield, as it may point to the defective pathway allowing scrutinizing genes in genomic data or vice versa: it generates evidence of the deleterious functional impact of a dna variants of unknown significance (vus). in this study we will unite our national expertises and apply a multi-omics approach to solve the unsolved genetic basis of patients with a metabolic phenotype on a larger scale. objective: integrating genomic (wes/wgs) and other -omics technologies in order to find the genetic causes, in 500 patients (children and adults) with an unexplained metabolic phenotype in whom standard care (genetic and metabolic evaluation) did not provide a diagnosis. study design: a prospective, diagnostic (deep phenotyping, wes/wgs and pan-omics) multicenter cohort study. study population: (in)capacitated patients (all ages/both genders) with a clinical (and/or family) history and abnormal additional examination (physical (neurological)/ biochemical/ radiological/ genetic) suspicious for an iem, without diagnosis. main study parameters/endpoints: 1) identification of a genetic variant and alignment with its biochemical and phenotypical abnormalities; 2) evaluating the diagnostic yield of combined wes/wgs and omics techniques methods used: patients with unexplained metabolic phenotypes are referred (on paper) and discussed by the zoemba (zoektocht naar erfelijke metabole aandoening) team. clinical phenotyping, bioinformatic reanalysis of wes data and additional metabolomics will be performed in all participants. in case still no diagnosis is made, a tailormade diagnostic plan is made combining deep wes, wgs, glycomics, lipidomics, epigenomics, transcriptomics and/or proteomics leading to: a known iem, a candidate variant or no diagnosis. in case of a variant, additional functional studies (enzymatic assays, targeted omics, crispr/cas, cell lines) will be performed to confirm the effect of the genetic variant on protein function. when still no diagnosis is established, matchmaking (genetic/phenotypical) through international databases might lead to a diagnosis. nature and extent of the burden and risks associated with participation, benefit and group relatedness: the study involves collection of clinical data, reanalysis of previously analysed genetic data, additional "omics" and functional testing. all participants will have between 1 and 3 clinical visits for this study (at the umc of referral ) and a maximum of 2 telephone appointments with the arts-onderzoeker. whenever possible study visits will be combined with regular hospital visits. clinical data (clinical history, family history, physical examination, consultations, additional laboratory and/or radiological investigations) will be collected. a physical examination and blood and urine sampling will be performed in all participants at their first study visit. any other already available biological samples (eg stored cell lines, dried blood spots, cerebrospinal fluid (csf)) will be collected for re-analysis. for a selection of patients a skin biopsy will be performed at the 2nd clinical study visit for the use of functional studies. potential burdens for participants are: the additional study visit(s), diagnostic procedures (e.g. blood, urine sampling and skin biopsy), as well as renewed (false) hope/uncertainty about finding a diagnosis. the potential benefit for all participants include: the opportunity to establish a diagnosis providing information on prognosis, (refinement of) management, genetic counselling with precise recurrence risk and option(s) for prenatal diagnosis.

Eligibility criteria:
inclusion criteria: patients with an unexplained metabolic phenotype defined as: neurological symptoms and/or abnormalities on (physical) examination suggestive of an inborn error of metabolism (energy deficiency, intoxication type or storage type): energy deficiency: neurological (repeated rhabdomyolysis, verified exercise intolerance, neuropathy, myopathy, ataxia), ophthalmological (retinitis pigmentosa (rp)), otological (hearing loss, deafness), endocrine (hypoparathyroidism, hypoglycemia) intoxication: neurological (encephalopathy, regression, movement disorder, psychiatric symptoms), ophthalmological (lens luxation), organic (liver and kidney function abnormalities) storage: neurological (regression, psychiatric symptoms), ophthalmological (cataract/corneal clouding), skin (angiokeratomas), blood (cytopenias), organic (hepatosplenomegaly, cardiac hypertrophy, skeletal abnormalities, short stature, coarse facial features, umbilical/inguinal hernia) and / or one or more of the following suggesting a deficient metabolic pathway or process: * abnormal metabolites in body fluids (csf, urine, blood) * functional studies at a biochemical/cellular level indicative of a metabolic deficiency (e.g. respiratory chain complex analysis) * organ dysfunction (e.g. liver or kidney failure) * an abnormal clinical function test (protein loading test, fasting test, meal test, validated exercise test, non-ischaemic underarm test) * abnormalities on imaging (neuro-imaging (including spectroscopy); x-rays (dysostoses or other bone abnormalities); ultrasound (enlarged liver/spleen)) * a vus (variant of unknown significance) in a gene involved in metabolism and no diagnosis despite extensive clinical, metabolic and genetic investigations * snp-array/array-cgh: inconclusive results * metabolic screening according to up to date clinical protocols: inconclusive results * wes (open or gene panel): no class 4 or 5 variants in a known (omim annotated) disease related gene that can fully explain the phenotype of the patient exclusion criteria: a patient will be excluded from participation in this study if: * after discussion by the zoemba team (see methods) he/she is suspected to have: * a genetic condition for which there is a simpler and more cost-effective test available for diagnosis * a complex genetic disorder (caused by a combination of multiple genes and/or environmental influences) * a condition that is thought to be caused by factors that are non-genetic, such as infection, injury or toxic exposure * he/she is unable to follow the study protocol (e.g. additional blood samples)

Keywords: wes wgs metabolomics diagnoses